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SG-Portfolio Test Problems for Stochastic Multistage Linear Programming
ISBN
3-540-60806-0
Type
conference paper
Date Issued
1995-09-13
Author(s)
Abstract
The solvability of dynamic decision problems suffers from the curse of dimensionality, which limits the planning horizon one can afford for mapping the real problem into a numerically solvable dynamic optimization model. In this note, stochastic multistage programming is applied to dynamic fixed-income portfolio selection. We report how well some fixed income portfolio problems are currently solved with barycentric approximation. In particular, we illustrate how the planning horizon affects the numerical effort required to solve the programs. The computational results serve as a benchmark for decomposition methods of mathematical programming.
Language
English
Keywords
Multistage Stochastic Programming
Barycentric Approximation
HSG Classification
not classified
Refereed
No
Book title
Operations Research Proceedings 1995
Publisher
Springer-Verlag
Publisher place
Berlin, DE
Start page
102
End page
107
Pages
6
Event Title
Symposium on Operations Research (SOR'95)
Event Location
Passau, DE
Subject(s)
Division(s)
Eprints ID
7223